The Methods in Computational Neuroscience (MCN) course at the Marine Biological Laboratory in Woods Hole, MA provides a singular training opportunity to equip students with cutting edge skills and conceptual foundations of computational methods applied to understanding the dynamics and function of brain cells, circuits, and behavior. MCN is an intense lecture and laboratory course-targeted to a talented and diverse pool of students. MCN students interact one-on-one with internationally renowned scientists and carry out hands-on, project-based training with a wide variety of computational techniques and approaches. A foundational goal of the MCN course is to prepare students to carry out research leading to 1) new theoretical and data analysis tools, and 2) conceptual foundations for understanding of the biological basis of mental processes. These goals directly align with the scientific vision of the BRAIN Initiative. The course provides in-depth instruction on how to use computational approaches to solve fundamental problems in neurobiology, and bridge the wide range of scales probed by different experimental techniques. This is accomplished through hands-on training in the mathematical foundations and techniques for the model- based analysis of neural data, in the context of mechanistic descriptions of neurons, networks, and brain systems. The MCN course maintains its innovative edge by continually updating computational topics that are relevant to new experimental advances, such as the identification of cell types with distinct cellular properties, high-resolution anatomy that provids information about connectivity and structural properties of neurons, large-scale neuronal recordings with high-density electrical and optical techniques, and causal interventions such as optogenetics. New topics in the course include emerging computational approaches such as compressed sensing, advanced statistical inference, optimal experimental design, dimensionality reduction and analysis of large data sets. An additional innovation is an increased emphasis on computational approaches to understanding and addressing brain disorders, including schizophrenia, epilepsy, addiction, depression, and Parkinson's disease. The course is unique in providing students intensive interactions with a group of dedicated faculty, many of whom devote weeks or even the entire month to work with students. The course fosters a collegial, international environment that advances student careers by providing students with networking opportunities that lead to long-term interactions, mentorship, and collaborations.

Public Health Relevance

The Methods in Computational Neuroscience Course (MCN) provides an exceptional and singular training opportunity that gives trainees a powerful set of tools for revealing the biological underpinnings of human brain disorders and developing causal approaches to treat them. This month-long course is characterized by a rigorous and innovative curriculum that teaches students how to use cutting-edge quantitative methods to statistically analyze the explosion of new data on brain function emerging from advanced experimental techniques, as well as to build powerful computer models of brain function in the normal and diseased state. The course places strong emphasis on computational approaches to understanding and addressing brain disorders, including schizophrenia, epilepsy, addiction, depression, and Parkinson's disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Education Projects (R25)
Project #
5R25MH062204-20
Application #
9733343
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Van'T Veer, Ashlee V
Project Start
2000-08-22
Project End
2020-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
20
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Marine Biological Laboratory
Department
Type
DUNS #
001933779
City
Woods Hole
State
MA
Country
United States
Zip Code
02543
Nguyen, Dieu My T; Roper, Mark; Mircic, Stanislav et al. (2017) Grasshopper DCMD: An Undergraduate Electrophysiology Lab for Investigating Single-Unit Responses to Behaviorally-Relevant Stimuli. J Undergrad Neurosci Educ 15:A162-A173
Kristensen, Anders S; Hansen, Kasper B; Naur, Peter et al. (2016) Pharmacology and Structural Analysis of Ligand Binding to the Orthosteric Site of Glutamate-Like GluD2 Receptors. Mol Pharmacol 89:253-62
Nishi, Rae; CastaƱeda, Edward; Davis, Graeme W et al. (2016) The Global Challenge in Neuroscience Education and Training: The MBL Perspective. Neuron 92:632-636
Okubo, Tatsuo S; Mackevicius, Emily L; Payne, Hannah L et al. (2015) Growth and splitting of neural sequences in songbird vocal development. Nature 528:352-7
Dagda, Ruben K; Thalhauser, Rachael M; Dagda, Raul et al. (2013) Using crickets to introduce neurophysiology to early undergraduate students. J Undergrad Neurosci Educ 12:A66-74
Roberts, C B; Best, J A; Suter, K J (2006) Dendritic processing of excitatory synaptic input in hypothalamic gonadotropin releasing-hormone neurons. Endocrinology 147:1545-55